Coherence bias mitigation through regularized tapered coherence matrix for phase linking in decorrelated environments

Abstract

Phase linking technique has shown the ability to mitigate the decorrelation effect on the time series interferometric synthetic aperture radar (InSAR) data. By imposing the temporal phase-closure constraint, this technique reconstructs a consistent phase series from the complex sample coherence matrix (SCM). However, the bias of coherence estimates degrades the performance of phase linking, especially in near-zero coherence environments with limited spatial sample support. In this study, we present a methodology to enhance phase linking, with an emphasis on SCM refinement. The incentive behind this is to shrink the tapered SCM towards a scaled identity matrix by exploiting the inner correlation and coherence loss trend in SCM. This allows debiasing the SCM magnitude even in the presence of small sample size. We demonstrate the performance of this method by simulations and real case studies using Sentinel-1 data over Hawaii island. Results from comprehensive comparisons validate the effectiveness of coherence matrix estimation and the enhancement to phase linking in different coherence scenarios. The source code and sample dataset are available at https://www.mathworks.com/matlabcentral/fileexchange/169553-insar-phase-linking-enhancement-by-scm-refinement.